OBJECTIVE -To determine the prevalence of a metabolic syndrome phenotype among U.S. adolescents using the most recent national data and to examine trends in metabolic syndrome prevalence.RESEARCH DESIGN AND METHODS -Analysis of data on 991 adolescents (aged 12-19 years) who had fasted for at least 6 h, from the National Health and Nutrition Examination Survey (NHANES 1999(NHANES -2000. The metabolic syndrome was determined using the National Cholesterol Education Program (Adult Treatment Panel III) definition modified for age.RESULTS -The overall prevalence of a metabolic syndrome phenotype among U.S. adolescents increased from 4.2% in NHANES III (1988-1992 to 6.4% in NHANES 1999 -2000 (P Ͻ 0.001). The syndrome was more prevalent (P Ͻ 0.01) in male than female adolescents (9.1 vs. 3.7%) and was found in 32.1% of overweight adolescents (BMI Ն95th percentile for age and sex), compared with 7.1% of adolescents at risk for overweight (BMI between 85th and 95th percentiles) (P Ͻ 0.001). Based on population-weighted estimates, Ͼ2 million U.S. adolescents currently have a metabolic syndrome phenotype.CONCLUSIONS -The prevalence of a metabolic syndrome phenotype has increased significantly over the past decade among U.S. adolescents and is particularly prevalent (Ͼ30%) in overweight adolescents. These findings have important implications for public health because of the well-known health risks associated with the metabolic syndrome in adults. Diabetes Care 27:2438 -2443, 2004A n association between obesity, high fasting triglycerides, elevated fasting plasma insulin, impaired glucose tolerance, hypertension, and cardiovascular disease (CVD) has been recognized since the early 1960s. These major risk factors tend to cluster together in many individuals, suggesting a common etiology, which has been variously termed Syndrome X, the insulin resistance syndrome, and the metabolic syndrome. The Third Report of the National Cholesterol Education Program (Adult Treatment Panel III [ATP III]) recognized the clustering of these major CVD risk factors, which was termed the metabolic syndrome, as a secondary target of riskreduction therapy (1). Current estimates indicate that the age-adjusted prevalence of the metabolic syndrome is roughly 24% among U.S. adults (2). The metabolic syndrome is largely confined to overweight and obese adults, with prevalence estimates of ϳ22% among adults with a BMI Ն25 and Ͻ30 kg/m 2 and 60% among adults with a BMI Ն30 kg/m 2 (3). In adults free of diabetes, having the metabolic syndrome independently predicts incident type 2 diabetes (4). The metabolic syndrome is also related to an increased risk of all-cause and CVD mortality in adults with (5) and without (6,7) type 2 diabetes, independent of other risk factors.Although it has been studied extensively in adults, much less is known about the metabolic syndrome in youth. Current estimates indicate that roughly 4% of U.S. adolescents have a metabolic syndrome phenotype, based on an agemodified definition of the ATP III criteria established for adu...

Many randomized experiments suffer from noncompliance. Some of these experiments, so-called encouragement designs, can be expected to have especially large amounts of noncompliance, because encouragement to take the treatment rather than the treatment itself is randomly assigned to individuals. We present an extended framework for the analysis of data from such experiments with a binary treatment, binary encouragement, and background covariates. There are two key features of this framework: we use an instrumental variables approach to link intention-to-treat effects to treatment effects and we adopt a Bayesian approach for inference and sensitivity analysis. This framework is illustrated in a medical example concerning the effects of inoculation for influenza. In this example, the analyses suggest that positive estimates of the intention-to-treat effect need not be due to the treatment itself, but rather to the encouragement to take the treatment: the intention-to-treat effect for the subpopulation who would be inoculated whether or not encouraged is estimated to be approximately as large as the intention-to-treat effect for the subpopulation whose inoculation status would agree with their (randomized) encouragement status whether or not encouraged. Thus, our methods suggest that global intention-to-treat estimates, although often regarded as conservative, can be too coarse and even misleading when taken as summarizing the evidence in the data for the effects of treatments.

BACKGROUND: Electronic information systems have been proposed as one means to reduce medical errors of commission (doing the wrong thing) and omission (not providing indicated care).

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